Module Handbook

You can use this search form for searching subject module.


Author: Prof. D. Garmaa

Topic Content:

•	Fundamental concepts of algorithm: Examples of simple algorithms, Definition of algorithm,  Properties of  algorithm, Common elements of algorithms(input, computation, selection, iteration, output), Methods of algorithm description(natural language, flow charts, programming language, pseudo-code)
•	Types of algorithms: Linear, branch and loop algorithms, types of loops
•	Design and analysis: Modeling the problem, Selecting numerical method to solve the problem, Testing algorithms, techniques for testing algorithms, Analyzing algorithms,  space and running time analysis,  the asymptotic  notations
•	 Types of  data: Arrays, sorting and searching algorithms, String,  string-matching algorithms 
•	Strategies of algorithms: Combinatorial algorithms, Sub-algorithm and Recursive algorithms,Greedy algorithms. 

 LEARNING OUTCOME: • In the context of specific algorithms, identify the characteristics of data and/or other conditions or assumptions that lead to different behaviors. • Determine informally the time and space complexity of simple algorithms. • State the formal definition of big O. • Implement and examine basic numerical algorithms. • Apply and employ Linear, branch and loop algorithms. • Impl